We have developed a system, Generalized cylinder Recognition Using Perceptual Organization (GRUPO), that performs model-based recognition of the projections of generalized cylinders. Motivated by psychological theory, the approach uses perceptual organization, the grouping of structurally significant features, to limit the object and viewpoint search spaces in recognition. The system receives feature data from a segmentation based on perceptual organization and ranks the object space according to estimates of conditional object probabilities. Depth information is not used in the approach.
To complete the recognition system, several problems were solved. For modeling, theoretical contributions include a proof for the invariance of discontinuities to projection, a method to find the axis of symmetry1, and a technique for determining self-occlusion. For the recognition process, solutions to search administration, feature matching, probabilistic search of the object space, and final template matching have been developed. The theory has been implemented and tested on synthetic data.